arXiv (All)
open access
JEV vs. LLMs as Rubric Judges: Cheaper, Faster, and Wrong in the Same Places
We ask whether Jev, a typed classifier that returns probabilities over permitted answers without generating text, can replace an LLM rubric judge. We compare it with three flash-tier LLM judges on nine panels drawn from seven benchmarks, giving every judge identical criterion texts. Jev's accuracy d
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- DIAL: Position-Debiased LLM Judges with Adaptive Human Preference Calibration#1105773
- Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?#821932
- Exploiting LLM-as-a-Judge Disposition on Free Text Legal QA via Prompt Optimization#124088
- Rubrics as an Attack Surface: Stealthy Preference Drift in LLM Judges#1109002
- Rubric-Aware On-Policy Self-Distillation for LLM Personalization#1129856
Record · ID 1077696
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive